Biology subjects

Solbakk, A.-K.

Publications and source records attributed to Solbakk, A.-K..

16 recordsLinked to original sources

bioRxiv2026

STAMP-LME: A spatiotemporal surface-mapping framework for population-level iEEG

Intracranial EEG (iEEG) affords a unique opportunity to assess human neural activity with millisecond temporal resolution and millimeter spatial precision. However, group-level statistical analyses remain challenging due to sparse and heterogeneous electrode coverage, anatomical variability, and the difficulty of integrating spatiotemporal responses across individuals. Most iEEG studies therefore define brain regions of interest for the group analysis, sacrificing a spatial resolution strength of iEEG and excluding data outside those regions of interest. Here, we present a spatiotemporal analysis and mapping with permutation-based linear mixed-effects models (STAMP-LME), a cortical-mapping framework for population-level iEEG analysis independent of predefined cortical regions of interest. STAMP-LME is a complete processing pipeline spanning electrode localization, mapping to a standardized surface of the cortical mantle, including medial, orbitofrontal, and insular regions, and statistical inference at the cortical level. Electrode-level data from each participant is mapped to a standardized cortical surface using weights that account for electrode-to-cortex distance and confidence in cortical sampling. Brain signals are then combined with a spatial smoothing kernel and entered into LME models at each vertex-node and time point. Data-derived null distributions are generated through controlled permutations and used for spatiotemporal inference with threshold-free cluster enhancement (TFCE) or false-discovery-rate (FDR) correction. We validated STAMP-LME using simulations with known cortical ground truth while varying effect size, interparticipant source-location variability, electrode coverage, and spatial smoothing. The framework reliably detected simulated effects and recovered their spatiotemporal distribution while maintaining low localization error and limiting false-positive detections across different sampling conditions. We then applied the method to intracranial recordings from nine individuals performing an auditory oddball task. The empirical analysis revealed distributed auditory cortical responses consistent with conventional channel-level analyses, while providing more fine-grained group-level activation maps across sampled cortical regions. STAMP-LME provides a flexible, open-source framework for data-driven population-level cortical iEEG analysis that preserves the spatiotemporal strengths of intracranial recordings while accounting for sparse and heterogeneous electrode coverage. The structured workflow enables reproducible and anatomically precise group-level inference on a standardized cortical surface and facilitates comparison with surface-based fMRI and source-localized M/EEG results, therefore providing a practical tool for cognitive and clinical neuroscience research.

neuroscience↗

bioRxiv2026

A single cortical circuit implements fast and slow visual search

How the brain produces different behaviors from a fixed anatomical substrate is a foundational question in neuroscience. The dominant account holds that behavioral flexibility requires distinct neural circuits: dedicated systems selectively recruited for different processing modes. An alternative proposes that flexibility arises not from switching between circuits, but from dynamically controlling the speed at which a shared circuit operates. Here, we test this account directly using intracranial EEG recordings from nineteen human patients performing two visual search tasks of markedly different difficulty: an easy color-singleton search and a difficult orientation search, a fast vs. slow dissociation attributed for four decades to distinct anatomical and oscillatory neural systems. We show that both search tasks recruit the same cortical regions, oscillatory frequencies, and processing hierarchy. Dynamic time warping reveals that the two neural trajectories are time-stretched versions of one another; the same temporal scaling appears within each condition between faster and slower trials, indexing response speed rather than the distinction between tasks. Alpha-band oscillations (~8-10 Hz) support this temporal scaling through two coordinated mechanisms: synchronizing activity across a posterior cortical network and phase-gating local high-frequency activity (70-150 Hz) within those regions at the same preferred phase in both conditions. These findings establish that, for the two tasks studied here, fast and slow visual search are not implemented by selecting between distinct dedicated circuits, but by adjusting the speed of a single alpha-coordinated architecture. The same principle may apply to other search tasks, and to other domains in which dual-process architectures have been invoked, a testable prediction for future studies.

neuroscience↗

bioRxiv2025

Brain Dynamics of Mental Manipulation

Humans effortlessly juggle their internal thoughts, but the neuronal dynamics that support mental manipulation are largely unknown. Leveraging the high spatiotemporal fidelity of intracranial recordings in humans (N = 30), we provide evidence that mental sound manipulation involves the inhibition of sensory cortex and the coordinated engagement of memory and control networks. This modulation manifests in two ways. First, there is a shift in the balance between faster (> 30 Hz) and slower (< 30 Hz) dynamics in primary and secondary auditory areas, suggesting a decrease in local excitability. Second, there is a distributed increase in oscillatory synchrony (6-10 Hz), which predicts imagery vividness and task performance. This evidence points to a key role of local excitability and inter-areal synchrony in the manipulation of thought.

neuroscience↗

bioRxiv2025

Predictive encoding of auditory sequences in the human prefrontal cortex

Humans extract regularities from the environment to form expectations that guide perception and optimize behavior. Although the prefrontal cortex (PFC) is central to this process, the relative contributions of orbitofrontal (OFC) and lateral PFC (LPFC) remain unclear. Here, we show that the brain tracks sound regularities in an auditory deviance detection task to predict when a target deviant will occur. Intracranial EEG in epilepsy patients reveals prefrontal engagement, with earlier expectancy-related modulation in OFC and later modulation in LPFC. Connectivity analyses indicate bidirectional and asymmetrical expectancy-related information exchange between the two areas, with a first lead by OFC, consistent with its role in initiating predictive encoding. Converging causal evidence shows that OFC lesions abolish sensitivity to expectancy, whereas LPFC lesions yield only modest effects not significantly different from controls. Together, these results provide electrophysiological and causal evidence for distinct, temporally organized contributions of prefrontal subregions to predictive processing. Significance StatementThe human brain builds probabilistic associations capturing the dynamic environmental structure in a predictive manner. The ability to encode and deploy predictive information to anticipate future events relies on the prefrontal cortex (PFC). However, the specific roles of PFC subregions in this process remain unclear. Here, we provide converging electrophysiological and causal lesion evidence on the distinct involvement of the orbital and lateral PFC in generating anticipatory neural signals based on probabilistic auditory structure.

neuroscience↗

bioRxiv2023

Predicting the Beat Bin - Beta Oscillations Support Top-Down Prediction of the Temporal Precision of a Rhythmic Event

Periodic sensory inputs entrain oscillatory brain activity, reflecting a neural mechanism that might be fundamental to temporal prediction and perception. Most environmental rhythms, such as music or speech, however, are rather quasi-periodic. Research has shown that neural tracking of speech is driven by modulations of the amplitude envelope, especially via sharp acoustic edges, which serve as prominent temporal landmarks. In the same vein, research on rhythm processing in music supports the notion that perceptual timing precision varies systematically with the sharpness of acoustic onset edges, conceptualized in the beat bin hypothesis. Increased envelope sharpness induces increased precision in localizing a sound in time. Despite this tight relationship between envelope shape and temporal processing, it is currently unknown how the brain uses predictive information about envelope features to optimize temporal perception. With the current study, we show that the predicted sharpness of the amplitude envelope is encoded by pre-target neural activity in the beta band (15-25 Hz), and has an impact on the temporal perception of sounds. Using probabilistic sound cues in an EEG experiment, we informed participants about the sharpness of the amplitude envelope of an upcoming target sound embedded in a quasi-isochronous beat. The predictive information about the envelope shape modulated the performance in the timing judgment task and pre-target beta power. Interestingly, these conditional beta-power modulations correlated positively with behavioral performance in the timing-judgment task and with perceptual temporal precision in a click-alignment task. This study provides new insight into the neural processes underlying prediction of the sharpness of the amplitude envelope during beat perception, which modulate the temporal perception of sounds. This finding could reflect a process that is involved in temporal prediction, exerting top-down control on neural entrainment via the prediction of acoustic edges in the auditory stream.

neuroscience↗

bioRxiv2023

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

Precise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations. To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first present GridFit, an algorithm that simultaneously localizes all contacts in grids, strips, or depth arrays by fitting flexible models to the electrodes CT artifacts. We observed localization errors of less than one millimeter (below 8% relative to the inter-electrode distance) and robust performance under the presence of noise, unrelated artifacts, and high-density implants when we ran [~]6000 simulated scenarios. Furthermore, we validated the method with real data from 20 intracranial patients. As a second registration step, we introduce CEPA, a brain-shift compensation algorithm that combines orthogonal-based projections, spring-mesh models, and spatial regularization constraints. When tested with real data from 15 patients, anatomical registration errors were smaller than those obtained for well-established alternatives. Additionally, CEPA accounted simultaneously for simple mechanical deformation principles, which is not possible with other available methods. Inter-electrode distances of projected coordinates smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Moreover, in an additional validation procedure, we found that modeling resting-state high-frequency activity (75-145 Hz) in five patients further supported our new algorithm. Together, GridFit and CEPA constitute a versatile set of tools for the registration of subdural grid, strip, and depth electrode coordinates that provide highly accurate results even in the most challenging implantation scenarios. The methods presented here are implemented in the iElectrodes open-source toolbox, making their use simple, accessible, and straightforward to integrate with other popular toolboxes used for analyzing electrophysiological data.

bioinformatics↗

bioRxiv2023

Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a Local-Global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation is impacted at two hierarchical levels of rule abstraction. HighlightsO_LIOrbitofrontal lesions reduce auditory MMN to unpredicted tones at the local level (between tones within sequences) of the rule hierarchy in the Local-Global paradigm. C_LIO_LIOrbitofrontal lesions also impact combined local and global (between sequences) level auditory deviance response, as manifested by diminished and delayed MMN and delayed P3a. C_LI

neuroscience↗

bioRxiv2022

Subspace partitioning in human prefrontal cortex resolves cognitive interference

Human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task-features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between co-existing representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.

neuroscience↗

bioRxiv2022

Quantifying Evoked Responses through Encoded Information

Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the t-test, is rare. Here, such a comparison is carried out by evaluating the novel method of Encoded Information with Mutual Information, Gaussian Copula Mutual Information, Neural Frequency Tagging, and t-test. We do so by applying each method to event-related potentials and event-related activity in different frequency bands originating from intracranial electroencephalography recordings of humans and marmoset monkeys. Encoded Information is a novel procedure that assesses the similarity of brain responses across experimental conditions by compressing the respective signals. Such an information-based encoding is attractive whenever one is interested in detecting where in the brain condition effects are present.

neuroscience↗

bioRxiv2022

Periodic neglect after frontoparietal lesions provides causal evidence for rhythmic attention sampling

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time even in states of presumed sustained attention. Recent evidence suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results uncovered that frontoparietal lesions introduce periodic neglect, i.e., temporally-specific behavioral deficits that were aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with healthy controls during optimal phases but attenuated during the less excitable sub-cycles. Theta-dependent sampling (3 - 8 Hz) was causally dependent on prefrontal cortex, while alpha-band sampling (8 - 14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high amplitude, low frequency brain activity is not epiphenomenal, but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

neuroscience↗

bioRxiv2022

Decision and response monitoring during working memory are sequentially represented in the human insula

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta and beta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

neuroscience↗

bioRxiv2021

Population coding and oscillatory subspace synchronization integrate context into actions

Contextual cues and prior evidence guide human goal-directed behavior. To date, the neurophysiological mechanisms that implement contextual priors to guide subsequent actions remain unclear. Here we demonstrate that increasing behavioral uncertainty introduces a shift from an oscillatory to a continuous processing mode in human prefrontal cortex. At the population level, we found that oscillatory and continuous dynamics reflect dissociable signatures that support distinct aspects of encoding, transmission and execution of context-dependent action plans. We show that prefrontal population activity encodes predictive context and action plans in serially unfolding orthogonal subspaces, while prefrontal-motor theta oscillations synchronize action-encoding population subspaces to mediate the hand-off of action plans. Collectively, our results reveal how two key features of large-scale population activity, namely continuous population trajectories and oscillatory synchrony, operate in concert to guide context-dependent human behavior.

neuroscience↗

bioRxiv2021

Modeling intracranial electrodes

BackgroundIntracranial electrodes are implanted in patients with drug-resistant epilepsy as part of their pre-surgical evaluation. This allows investigation of normal and pathological brain functions with excellent spatial and temporal resolution. The spatial resolution relies on methods that precisely localize the implanted electrodes in the cerebral cortex, which is critical for drawing valid anatomical inferences about brain function. Multiple methods have been developed to localize implanted electrodes, mainly relying on pre-implantation MRI and post-implantation CT images. However, there is no standard approach to quantify the performance of these methods systematically. The purpose of our work is to model intracranial electrodes to simulate realistic implantation scenarios, thereby providing methods to optimize localization algorithm performance. ResultsWe implemented novel methods to model the coordinates of implanted grids, strips, and depth electrodes, as well as the CT artifacts produced by these. We successfully modeled a large number of realistic implantation "scenarios", including different sizes, inter-electrode distances, and brain areas. In total, more than 3300 grids and strips were fitted over the brain surface, and more than 850 depth electrode arrays penetrating the cortical tissue were modeled. More than 37000 simulations of electrode array CT artifacts were performed in these "scenarios", mimicking the intensity profile and orientation of real artifactual voxels. Realistic artifacts were simulated by introducing different noise levels, as well as overlapping electrodes. ConclusionsWe successfully developed the first platform to model implanted intracranial grids, strips, and depth electrodes and realistically simulate CT artifacts and noise. These methods set the basis for developing more complex models, while simulations allow the performance evaluation of electrode localization techniques systematically. The methods described in this article, and the results obtained from the simulations, are freely available via open repositories. A graphical user interface implementation is also accessible via the open-source iElectrodes toolbox.

bioinformatics↗

bioRxiv2020

Orbitofrontal lesion patients show an implicit approach bias to angry faces

Damage to the ventromedial prefrontal cortex (VMPFC) can cause maladaptive social behavior, but the cognitive processes underlying these behavioral changes are still uncertain. Here, we tested whether patients with acquired VMPFC lesions show altered approach-avoidance tendencies to emotional facial expressions. Thirteen patients with focal VMPFC lesions and 31 age- and gender-matched healthy controls performed an implicit approach-avoidance task in which they either pushed or pulled a joystick depending on stimulus color. While controls avoided angry faces, VMPFC patients displayed an incongruent response pattern characterized by both increased approach and reduced avoidance of angry facial expressions. The approach bias was stronger in patients with higher self-reported impulsivity and disinhibition, and in those with larger lesions. We further used linear ballistic accumulator modelling to investigate latent parameters underlying approach-avoidance decisions. Controls displayed negative drift rates when approaching angry faces, whereas VMPFC lesions abolished this pattern. In addition, VMPFC patients had weaker response drifts than controls during avoidance. Finally, patients showed reduced drift rate variability and shorter non-decision times, indicating impulsive and rigid decision-making. Our findings thus suggest that VMPFC damage alters the pace of evidence accumulation in response to social signals, eliminating a default, protective avoidant bias and facilitating dysfunctional approach behavior.

neuroscience↗

bioRxiv2020

Intracranial recordings demonstrate medial temporal lobe engagement in visual search in humans

Visual search is a fundamental human behavior, which has been proposed to include two component processes: inefficient search (Search) and efficient search (Pop-out). According to extant research, these two processes map onto two separable neural systems located in the frontal and parietal association cortices. In the present study, we use intracranial recordings from 23 participants to delineate the neural correlates of Search and Pop-out with an unprecedented combination of spatiotemporal resolution and coverage across cortical and subcortical structures. First, we demonstrate a role for the medial temporal lobe in visual search, on par with engagement in frontal and parietal association cortex. Second, we show a gradient of increasing engagement over anatomical space from dorsal to ventral lateral frontal cortex. Third, we confirm previous work demonstrating nearly complete overlap in neural engagement across cortical regions in Search and Pop-out. We further demonstrate Pop-out selectivity manifesting as activity increase in Pop-out as compared to Search in a distributed set of sites including frontal cortex. This result is at odds with the view that Pop-out is implemented in low-level visual cortex or parietal cortex alone. Finally, we affirm a central role for the right lateral frontal cortex in Search.

neuroscience↗

bioRxiv2018

Auditory deviance detection in the human insula: An intracranial EEG study

While the human insula is known to be involved in auditory processing, knowledge about its precise functional role and the underlying electrophysiology is limited. To assess its role in automatic auditory deviance detection we analyzed the high frequency EEG activity (75-145 Hz) from 90 intracranial insular electrodes across 16 patients who were candidates for resective epilepsy surgery while they passively listened to a stream of standard and deviant tones. Deviant and standard tones differed in four physical dimensions: intensity, frequency, location and time. Auditory responses were found in the short and long gyri, and the anterior, superior, and inferior segments of the circular sulcus of the insular cortex, but only a subset of electrodes in the inferior segment showed deviance detection responses, i.e. a greater and later response to deviants relative to standards. Altogether, our results indicate that the human insula is engaged during auditory deviance detection.

neuroscience↗